Control theory MHKAR2S01003

Course content:
Mathematical modeling of multi input multi output control systems. State space equations- their formulation and solution. Analyzing the stability of control systems - Lyapunov methods. Canonical forms. Transformations to state space canonical forms. Transfer functions and state space equations - basics, transformations. Discrete-time models of control systems. Controlability and observability of control systems. Performance and sensitivity of control systems. Multi input multi output control systems - structures, decoupling and compensation. Control methods in time domain. Pole placement methods, Optimal control - Hamilton-Bellman principle, Pontriagin principle. Kalman filter. Optimal control methods - LQR.

Learning outcomes:
The student:
* defines models of multi input multi output (MIMO) control systems, defines controlability, observability of control systems, knows state space description of control systems, knows canonical forms and decoupling methods for MIMO control systems,
* formulates and recognizes methods of stability analysis, knoed the relation between transfer function based models and state space models, defines performance indexes and sensitivity functions of control systems,
* presents discrete-time models of control systems, control methods in time domain, pole placement methods, optimal control methods and Kalman filters,
* formulates and solves analytically state space equations, transforms to state space canonical forms, transforms from transfer function models to state space models and vice versa,
* can test analytically stability, controlability, observability of control systems, can design the state controller using the pole placement methods and LQR methods,
* uses Matlab/Simulink to model, analyze (in time and frequency domains) conrol systems, design PID, state and LQR controllers, state space observers, Kalman filters and canonical forms of control systems,
* works in a team